Optimisation of the Flow Process in Engine Bays - 3D Modelling of Cooling Airflow

Doctoral thesis, 2011

The focus of today’s automotive industry is to reduce emissions and fuel consumption of all vehicles. Concentrating on the truck industry, the last 20 years have focused largely on cutting emissions of particulate matter and nitrogen oxides. For the future, attention will be on fuel consumption and emissions of carbon dioxide. Significant changes have been made to fulfill new emission legislations, but the basic vehicle architecture has been kept. New after treatment systems that increases the thermal loading of the cooling system have been added within the same packaging envelope as before. This means that there is less space to evacuate cooling airflow today and more airflow than ever is required. Furthermore, project costs have increased over the years, focus is also on cutting cost and lead times. Thus virtual development early in the project is highly desirable. Long before any prototypes are available, companies must now answer the question; will this truck have competitive performance? As the project progresses, redesigns become more expensive. Development time is becoming more and more limited, meaning any changes tend to become major changes. This has lead to a new focus of detailed and accurate simulations of vehicle performance. For these reasons, in the context of underhood thermal management, this project has been carried out; to improve and optimise the flow process in engine bays. 3D CFD supported by 1D models and measurements has been studied to predict the cooling airflow in the engine bay of trucks. The conclusions are that there are good opportunities to simulate the flow process in engine bays early in development projects. This research project presents several different methods that, for different degrees of effort deliver different accuracy and indications are that simulation can replicate measurements. This is though, with advanced simulation models and a lot of computational effort, at least seen from today’s perspective.